Quantifying Uncertainty in Allometric Models: Fake Forests for the Real World

In calculating biomass using allometric equations, often there are choices of what published equation to use for a particular tree. The uncertainty associated with this choice is rarely reported. To examine the impacts of allometric equation choice on levels of uncertainty, we performed a thought experiment by creating a fake forest with characteristics similar to Mexican forests in terms of diameter distribution and a 'known' biomass with 100,000 individuals. An optimal sample size (n) and distribution of diameters for an allometric equation were calculated. From here, we analyzed the effects of n, distribution of n, range of n, and equation form on the uncertainty estimates of biomass for the forest as a whole. This work tries to illuminate the effects of allometric equation choice on uncertainty for forest inventories, such as that of Mexico, where a decision tree algorithm has been created to select the most appropriate equation from their equation database. This is an effort to reduce overall uncertainty in carbon estimates for structurally heterogeneous and biodiverse forests.